The role involves leading the full lifecycle of AI model development while setting technical strategy to ensure machine learning solutions achieve business impact. The individual will define the AI roadmap, establish engineering best practices, and foster a culture of responsible machine learning. Responsibilities include managing and mentoring engineering teams, overseeing end-to-end data science workflows, and ensuring statistical rigor in experimental design. The position requires leading technical discovery with enterprise clients and presenting AI strategies to senior stakeholders. Additionally, the role involves establishing production standards for model deployment, monitoring, and governance across cloud platforms.

Candidates must possess a Bachelor’s or Master’s degree in a quantitative field, with a Ph.D. strongly preferred. At least 10 years of progressive experience in data science and machine learning is required, including a minimum of 3 to 5 years in a leadership or management capacity. Applicants must demonstrate deep expertise in designing custom transformer architectures and a strong foundation in applied data science. The role requires proficiency in Python, core machine learning libraries, and large-scale data platforms, alongside experience in MLOps and cloud deployment.